@InProceedings{MiguelReyes2011,
author="Miguel Reyes
and Gabriel Dominguez
and Sergio Escalera",
title="Feature Weighting in Dynamic Time Warping for Gesture Recognition in Depth Data",
booktitle="1st IEEE Workshop on Consumer Depth Cameras for Computer Vision",
year="2011",
pages="1182--1188",
abstract="We present a gesture recognition approach for depth video data based on a novel Feature Weighting approach within the Dynamic Time Warping framework. Depth features from human joints are compared through video sequences using Dynamic Time Warping, and weights are assigned to features based on inter-intra class gesture variability. Feature Weighting in Dynamic Time Warping is then applied for recognizing begin-end of gestures in data sequences. The obtained results recognizing several gestures in depth data show high performance compared with classical Dynamic Time Warping approach.",
optnote="HuPBA;MILAB",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=1893), last updated on Tue, 11 Mar 2014 15:35:05 +0100",
isbn="978-1-4673-0062-9",
doi="10.1109/ICCVW.2011.6130384",
opturl="http://dx.doi.org/10.1109/ICCVW.2011.6130384"
}